SPEECH AND MULTIMODAL

Workshop

CURIN AI Faculties Attended RPA Workshop At NITTTR Chandigarh From 22-26 July 2019. CURIN faculty members Dr Luxmi Dapra, Dr Nitin Goyal and Dr Virender Kadyan of the M Tech (AI) course attended the week long training at NITTTR, Chandigarh on Robotic Process Automation being conducted by UiPath.
Dr. Virender Kadyan Conducted Speech Recognition Using Machine Learning Steam School Workshop From 18-22 Feb 2019 Dr Virender Kadyan Assistant Professor-Research and his team members Ms Sashi Bala, Mr Puneet Bawa and Mr Rishab researchers of Speech & Multimodal Laboratory has conducted the Batch-II of Steam School 2019 workshop on Speech Recognition using Machine learning from 18-22 Feb 2019. Dr Kadyan gave an introductory session on Machine learning approaches in aspects of recognition of uttered words. Day 2 has been designed so that students can perform Hands on sessions on Speech to text recognition systems. On day3 students learnt about the formation of Chat Bots and also tried to embed it with uttered speech signals. Finally students build their own Chat Bots on Day4 and day5 with sample text corpus in Hindi or English languages.
Dr Virender Kadyan Organised 10 Days Research Induced Training-V From 18 Dec To 29 Dec 2018 Dr Virender Kadyan Assistant Professor CURIN has organised 10 Days Research Induced Training-V from 18 Dec to 29 Dec 2018o. The training involved four modules for BE/BCA students of Chitkara University. Valedictory of the event is graced with presence of Chief Guest Dr Archana Mantri Pro-VC CURIN and Dr S N Panda Director Research along with faculty members.
Dr Virender Kadyan Assistant Professor Has Conducted The Day 2 Of Introduction To Linux Steam School 2018 Dr Virender Kadyan Assistant Professor CURIN has conducted the day2 of Introduction to Linux Steam School 2018. He has taught the basics of shell scripts. Students have performed hands-on practice on their Linux machines with some scenario based examples.
Summer School On Research Trends In Network Security, Machine And Deep Learning, Image And Multimedia Processing, June 2018 10 days summer school is successfully organized on Research Trends in Network Security, Machine and Deep Learning, Image and Multimedia Processing by Dr K R Ramkumar in support with Dr Shefali Dr Deepika Kaundal Dr Virender kadyan and Er Sarvesh CURIN. Participants gain knowledge on interdisciplinary areas of different research domains. Participants learned the art of writing a research paper. Around 52 research papers are generated as an outcome of the workshop.
Techno Sounds Techno Sounds 2016 Ist and IInd round were held on 13 October 2016 and 10 November 2016 at Speech and Multimodal Laboratory in association with CSI student Chapter at Chitkara University, Punjab.Er. Virender Kadyan, Assistant Professor, shared in brief about Techno Sounds 2016 and provide opportunity to students to show case their innovative ideas. A total of 24 teams registered for the event in the Ist round, out of which 9 teams got selected for second round to represent the prototype of their ideas. Mr. Vinay Kukreja, Assistant Professor , CSE department and Mr. Jaswinder Singh, Assistant Professor, CA department judged the event. The event was succesfully managed by Ms. Kanika and event coordinators. Further, shortlisted teams were qualified for the IIIrd round held on 24 January 2017, in which students had to showcase their complete product.
Summer School Chitkara University Research and Innovation Network (CURIN) had organised a Summer School from June 20, 2016 to July 2, 2016. This Summer School included 16 workshops in most relevant topics of research and academics ranging from Computer Science, Electronics and Communication to Mechanical Engineering. These workshops were specially designed to cater the need of state of the art research and development in forefront areas. The main goal of the Summer School was to provide knowledge to students, research scholars and academicians to start research and development in pioneer research areas.
ASR using Word Based Modeling, 18 March, 2016 Dr. Amitoj Singh (Assistant Director-Research) and Er. Virender Kadyan (Assistant Professor-Research) organized one day workshop on Hindi ‘ASR using Word Based Modeling’ at CU, Himachal campus. The audiences for this workshop included the students of CSE/ECE department. This workshop threw light on practical feasibility of making ASR for own language. Dr Amitoj began his talk by giving an introduction to Language Processing and its importance in a researcher’s life. The focus was on how to select and process a particular language. He then explained present state of availability of ASR system in Indian Language. In another session, Er Virender, gave a hands-on experience on How to recognize a particular word in Hindi language using HTK toolkit. He addressed the use of various acoustic modeling technique to process a small vocabulary Hindi ASR system
Automatic Speech Recognition , 9-10th Oct, 2015 Dr. Amitoj Singh, Assistant Director, Mr. Virender Kadyan, Assistant Professor and Mr. Vinay Kukreja, Assistant Professor, CURIN, CU, Punjab conducted a two-day workshop on “Automatic Speech Recognition” under ACM Student Chapter. Guest speakers enriched the workshop with their knowledge and skills and imparted practical sessions to engross students for inter-relating theoretical skills with practical implementation. Dr. Sumapreet Kaur from Punjabi University, Patiala gave an introduction on Phonology and Linguistics. Mrs. Rupinder Kaur from Thapar University, Patiala encouraged a hands-on session for building ASR system using HTK. Dr. Wiqas Ghai imparted hands-on session on Phone Based Modelling using HTK. The workshop emphasized an active participation of students as well as faculty members from within and outside University.

Publication

YEAR 2021

• Bawa, P., and Kadyan, V. (2021). Noise robust in-domain children speech enhancement for automatic Punjabi recognition system under mismatched conditions. Applied Acoustics, 175, 107810. https://doi.org/10.1016/j.apacoust.2020.107810

  Abstract: Success of any commercial Automatic Speech Recognition (ASR) system depends upon availability of its training data. Although, it's performance gets degraded due to absence of enough signal processing characteristics in less resource language corpora. Development of Punjabi Children speech system is one such challenge where zero resource conditions and variabilities in children speech occurs due to speaking speed and vocal tract length than that of adult speech. In this paper, efforts have been made to build Punjabi Children ASR system under mismatched conditions using noise robust approaches like Mel Frequency Cepstral Coefficient (MFCC) or Gammatone Frequency Cepstral Coefficient (GFCC). Consequently, acoustic and phonetic variations among adult and children speech are handled using gender based in-domain training data augmentation and later acoustic variability among speakers in training and testing sets are normalised using Vocal Tract Length Normalization (VTLN). We demonstrate that inclusion of pitch features with test normalized children dataset has significantly enhanced system performance over different environment conditions i.e clean or noisy. The experimental results show a relative improvement of 30.94% using adult female voice pooled with limited children speech over adult male corpus on noise based training data augmentation respectively.

• Kadyan, V., Bala, S. and Bawa, P. Training augmentation with TANDEM acoustic modelling in Punjabi adult speech recognition system. Int J Speech Technol (2021). https://doi.org/10.1007/s10772-021-09797-0

  Abstract:Processing of low resource pre and post acoustic signals always faced the challenge of data scarcity in its training module. It’s difficult to obtain high system accuracy with limited corpora in train set which results into extraction of large discriminative feature vector. These vectors information are distorted due to acoustic mismatch occurs because of real environment and inter speaker variations. In this paper, context independent information of an input speech signal is pre-processed using bottleneck features and later in modeling phase Tandem-NN model has been employ to enhance system accuracy. Later to fulfill the requirement of train data issues, in-domain training augmentation is perform using fusion of original clean and artificially created modified train noisy data and to further boost this training data, tempo modification of input speech signal is perform with maintenance of its spectral envelope and pitch in corresponding input audio signal. Experimental result shows that a relative improvement of 13.53% is achieved in clean and 32.43% in noisy conditions with Tandem-NN system in comparison to that of baseline system respectively.

YEAR 2020

• Taniya, V. Bhardwaj and V. Kadyan, "Deep Neural Network Trained Punjabi Children Speech Recognition System Using Kaldi Toolkit," 2020 IEEE 5th International Conference on Computing Communication and Automation (ICCCA), Greater Noida, India, 2020, pp. 374-378, doi: 10.1109/ICCCA49541.2020.9250780.

  Abstract: Despite the number of developed Automatic Speech Recognition (ASR) systems for different languages, still no work has been done on children's speech of Punjabi language. Due to the unavailability of children's speech corpus for Punjabi Language, it is a challenging task to collect speech data. In our current work, efforts have been made to collect Punjabi children's speech corpus and build Children ASR system for Indian regional Punjabi language. The recognition rate of ASR systems is observed to be improved drastically by the emergence of Deep Neural Networks (DNN). In our work, the DNN acoustic model has been implemented by varying number of hidden layers. Approximately four hours of Punjabi children's speech corpus has been collected and several experiments have been performed using the DNN modeling technique. Experimental results have revealed that the system has attained 87% accuracy.

• Bhardwaj, V., Bala, S., Kadyan, V., & Kukreja, V. (2020, July). Development of Robust Automatic Speech Recognition System for Children's using Kaldi Toolkit. In 2020 Second International Conference on Inventive Research in Computing Applications (ICIRCA) (pp. 10-13). IEEE. https://doi.org/10.1109/ICIRCA48905.2020.9182941

  Abstract: In this paper, the Punjabi children speech recognition system is developed using Subspace Gaussian mixture models (SGMM) acoustic modeling techniques. Initially, the system is dependent upon Mel-frequency cepstral coefficients (MFCC) approach for controlling the temporal variations in the input speech signals. Here, SGMM is integrated with HMM to measure the efficiency of each state which carries the information of a short-windowed frame. For handling the children speaker acoustic variations speaker adaptive training (SAT), based on vocal-tract length normalization and feature space maximum likelihood linear regression is adopted. Kaldi and open-source speech recognition toolkit is used to develop the Robust Automatic Speech Recognition (ASR) System for Punjabi Children's speech. S GMM accumulate the frame coefficients and their posterior probabilities and pass these probabilities to HMM which systematically fit the frame and output have resulted from HMM states. Therefore, the achievement of SGMM has gotten a large performance margin in Punjabi children speech recognition. A remarkable depletion in the word error rate (WER) was noticed using SGMM by varying the feature dimensions. The developed children ASR system obtained a recognition accuracy of 83.66% while tested by varying the feature dimensions to 12.

• Kaur, H., & Kadyan, V. (2020). Feature Space Discriminatively Trained Punjabi Children Speech Recognition System Using Kaldi Toolkit. Available at SSRN 3565906. http://dx.doi.org/10.2139/ssrn.3565906

  Abstract: Despite significant progress has been made in building of ASR system for various adult speech, whereas the children ASR system is still in infant stage for Indian languages. To build Punjabi children speech recognition is one such challenge because of unavailability of zero-speech corpus. In this paper, efforts have been made to build small vocabulary Punjabi continuous children speech corpus. In explored system, four variations of bMMI discriminative techniques have been perform on two context models: Dependent and Independent. Experiment result have shown that system attains Relative Improvement (RI) of 22-26% on fbMMI and fMMI acoustic model as compared to other approaches. Various combination of parameter has been implemented with variation in boosted parameter and iteration values to obtain optimal value of bMMI and fbMMI acoustic models.

• Kadyan, V., Mantri, A. & Aggarwal, R.K. Improved filter bank on multitaper framework for robust Punjabi-ASR system. Int J Speech Technol 23, 87–100 (2020). https://doi.org/10.1007/s10772-019-09654-1

  Abstract: Robustness of the automatic speech recognition (ASR) system relies upon the accuracy of feature extraction and classification in training phase. The mismatch between training and testing conditions during classification of large feature vectors causes a low performance. In this paper, the issue of robustness of acoustic information is addressed for practical Punjabi dataset. Traditional feature extraction approaches: mel frequency cepstral coefficients (MFCC) and gammatone frequency cepstral coefficients (GFCC) face the issue of high variance with leakage of spectral information. Also, handling of the huge number of feature information creates chaos for large speech vocabulary. To overcome this dilemma, a Principal component analysis (PCA) based multi-windowing technique is proposed with the incorporation of baseline GFCC and MFCC based feature approaches after the tuning of taper parameter. The proposed integrated approaches result in better feature vectors, which are further processed using differential evolution + hidden Markov model (DE + HMM) based modelling classifier. The integrated approaches show substantial performance for word recognition as compared to the conventional or fused feature extraction systems.

• Kadyan, V., & Kaur, M. (2020). SGMM-Based Modeling Classifier for Punjabi Automatic Speech Recognition System. In Smart Computing Paradigms: New Progresses and Challenges (pp. 149-155). Springer, Singapore. https://doi.org/10.1007/978-981-13-9680-9_12

  Abstract: A baseline ASR system does not perform better due to improper modeling of training data. Training of system through conventional HMM technique faced the issue of on or near manifold in data space. In this paper, Hybrid SGMM-HMM approach is compared with baseline GMM-HMM technique on Punjabi continuous simple sentences speech corpus. It examined the hybridized HMM technique: SGMM-HMM to overcome the problem of sharing of state parameter information throughout the training and testing of system. The system testing is performed on Kaldi 4.3.11 toolkit using MFCC and GFCC approaches at the front end of the system. The result obtained on SGMM-HMM modeling technique generates an improvement of 3–4% over GMM-HMM approach. The experiments are performed on real environment dataset.

• Kapoor, R., Kadyan, V., & Ahuja, S. (2019). Identification of Influential Parameter for Early Detection of Dengue Using Machine Learning Approach. Available at SSRN 3511419. http://dx.doi.org/10.2139/ssrn.3511419

  Abstract: Dengue is a viral disease which affects public health every year in global wise. Every change in climate in a particular location increases the probability of spreading dengue disease in that domain. There are number of health schemes running by governments to prevent and control dengue disease at early stages. The usage of information technology helps to achieve this goal. There is a huge need to develop machines which enable medical technicians to detect dengue disease at early stages. For achieving this goal, the author efforts to detect dengue dataset which helpful to develop a machine learning prediction model for dengue disease. The author conducts analytical study by collecting symptoms and clinical tests conducting by researcher in the same domain. To detect important factors of dengue, the author uses the statistical and support machine. Here, author effort shows four important factors fever, headache, skin rash and abdominal pain used to detect dengue at early stage.

YEAR 2019

• Singh, A., Kadyan, V., Kumar, M., & Bassan, N. (2019). ASRoIL: a comprehensive survey for automatic speech recognition of Indian languages. Artificial Intelligence Review, 1-32. https://doi.org/10.1007/s10462-019-09775-8

  Abstract: India is the land of language diversity with 22 major languages having more than 720 dialects, written in 13 different scripts. Out of 22, Hindi, Bengali, Punjabi is ranked 3rd, 7th and 10th most spoken languages around the globe. Expect Hindi, where one can find some significant research going on, other two major languages and other Indian languages have not fully developed Automatic Speech Recognition systems. The main aim of this paper is to provide a systematic survey of the existing literature related to automatic speech recognition (i.e. speech to text) for Indian languages. The survey analyses the possible opportunities, challenges, techniques, methods and to locate, appraise and synthesize the evidence from studies to provide empirical answers to the scientific questions. The survey was conducted based on the relevant research articles published from 2000 to 2018. The purpose of this systematic survey is to sum up the best available research on automatic speech recognition of Indian languages that is done by synthesizing the results of several studies.

• Kaur, H., Koundal, D., & Kadyan, V. (2019, April). Multi Modal Image Fusion: Comparative Analysis. In 2019 International Conference on Communication and Signal Processing (ICCSP) (pp. 0758-0761). IEEE. doi: https://doi.org/10.1109/ICCSP.2019.8697967

  Abstract: Image fusion acts as a powerful tool in the medical domain. It is an essential method for enhancing the quality of images by combining the complementary images which are captured from various sensors or cameras. The aim of multi modal image fusion technique is to obtain a single fused image by fusing the images of different modalities. It is widely used in various clinical applications for better diagnosis of several types of diseases. In this paper, comparative analysis has been made using various multi modal techniques in medical domain such as guided filter, multi resolution singular value decomposition and principal component analysis. The quantitative and qualitative results have been taken. The experiment results indicated that guided filter method is more efficient as compared to other methods in terms of evaluation metrics such as standard deviation is 29.8, mean is 52.3, entropy is 2.8 and fusion information score is 0.8. It has also been observed that guided filter is able to preserve edges efficiently and is more suitable for real applications.

• Kadyan, V., Mantri, A., Aggarwal, R. K., & Singh, A. (2019). A comparative study of deep neural network based Punjabi-ASR system. International Journal of Speech Technology, 22(1), 111-119. https://doi.org/10.1007/s10772-018-09577-3

  Abstract: HMM is regarded as the leader from last five decades for handling the temporal variability in an input speech signal for building automatic speech recognition system. GMM became an integral part of HMM so as to measure the efficiency of each state that stores the information of a short windowed frame. In order to systematically fit the frame, it reserves the frame coefficients and connects their posterior probability over HMM state that acts as an output. In this paper, deep neural network (DNN) is tested against the GMM through utilization of many hidden layers which helps the DNN to successfully evade the issue of overfitting on large training dataset before its performance becomes worse. The implementation DNN with robust feature extraction approach has brought a high performance margin in Punjabi speech recognition system. For feature extraction, the baseline MFCC and GFCC approaches are integrated with cepstral mean and variance normalization. The dimension reduction, decorrelation of vector information and speaker variability is later addressed with linear discriminant analysis, maximum likelihood linear transformation, SAT, maximum likelihood linear regression adaptation models. Two hybrid classifiers investigate the conceived acoustic feature vectors: GMM–HMM, and DNN–HMM to obtain improvement in performance on connected and continuous Punjabi speech corpus. Experimental setup shows a notable improvement of 4–5% and 1–3% (in connected and continuous datasets respectively).

• Arora, A., Kadyan, V., & Singh, A. (2019). Effect of tonal features on various dialectal variations of Punjabi language. In Advances in Signal Processing and Communication (pp. 467-475). Springer, Singapore. https://doi.org/10.1007/978-981-13-2553-3_45

  Abstract: Punjabi is tonal as well as under resource language among all the Indo Aryan languages of the Indo-European family. A vast number of variations in language lead to challenges while designing an Automatic Speech Recognition (ASR) system. Therefore, it turned out to be a matter of extreme concern to study the essential features such as tone of the language for designing an effective ASR. This paper lays its focus upon the variation of tonal characteristics of Punjabi dialect. The speech corpus has been collected from native speakers of Punjab (including all the various dialects) and also covering the areas under the Himachali belt of Punjab. The result analysis shows that tonal words and dialectal word information caste a major impact on the information conveyed by the speaker. The analyzed data shows pitch variations in tonal words that vary from region to region. The experiments are performed by using Praat toolkit for calculating F0 value; then depending upon the pitch and frequency variations, we have studied that tonal words show dialectal variations when the similar sentence is spoken by speakers of different regions.

• Bassan, N., & Kadyan, V. (2019). An Experimental Study of Continuous Automatic Speech Recognition System Using MFCC with Reference to Punjabi Language. In Recent Findings in Intelligent Computing Techniques (pp. 267-275). Springer, Singapore. https://doi.org/10.1007/978-981-10-8639-7_28

  Abstract: Punjabi language has almost 105 million native speakers and faced the challenge of less resource. The Punjabi ASR system has little research as compared to other Indian languages. This paper examines the continuous vocabulary of Punjabi language using Sphinx toolkit. The proposed work has been implemented on speaker-independent and speaker-dependent speakers in different environmental conditions. The Punjabi ASR system has been trained on 442 phonetically rich sentences using 15 speakers (6 Male and 9 female). The system adopts MFCC at the front end and HMM at the modelling phase to extract and classify feature vectors. The simulation result demonstrates the performance improvement of 93.85% on speaker-dependent dataset and 89.96% on speaker-independent dataset.

YEAR 2018

• Kadyan, V., Mantri, A., & Aggarwal, R. K. (2018). Refinement of HMM model parameters for Punjabi automatic speech recognition (PASR) System. IETE Journal of Research, 64(5), 673-688. https://doi.org/10.1080/03772063.2017.1369370

  Abstract: An automatic speech recognition system follows an approach of pattern matching, which consists of a training phase and testing phase. Despite advancement in training phase, the performance of the acoustic model is adverse while adopting the statistical technique like hidden Markov model (HMM). However, HMM-based speech system faces high computational complexity and becomes challenging to provide accuracy during isolated Punjabi lexicon. As the corpus of the system increases, the complexity of training phase will also increase drastically. The redundancy and confusion occurred between feature distributions in training phase of the system. This paper proposes an approach for the generation of HMM parameters using two hybrid classifiers such as GA+HMM and DE+HMM. The proposed technique focuses on refinement of processed feature vectors after calculating its mean and variance. The refined parameters are further employed in the generation of HMM parameters that help in reduction of training complexity of the system. The proposed techniques are compared with an existing technique such as HMM on benchmark databases and self-developed corpus in clean, noisy, and real-time environments. The results show the performance improvement in pattern matching of spoken utterance when demonstrated on large vocabulary isolated Punjabi lexicons.

Year 2017

• V. Kadyan, A., Mantri, & R. K. Aggarwal, “A heterogeneous speech feature vectors generation approach with hybrid hmm classifiers”. International Journal of Speech Technology, 20(4), 761-769, 2017

  Abstract: Automatic speech recognition (ASR) system plays a vital role in the human–machine interaction. ASR system faces the challenge of performance degradation due to inconsistency between training and testing phases. This occurs due to extraction and representation of erroneous, redundant feature vectors. This paper proposes three different combinations at speech feature vector generation phase and two hybrid classifiers at modeling phase. In feature extraction phase MFCC, RASTA-PLP, and PLP are combined in different ways. In modeling phase, the mean and variance are calculated to generate the inter and intra class feature vectors. These feature vectors are further adopted by optimization algorithm to generate refined feature vectors with traditional statistical technique. This approach uses GA + HMM and DE + HMM techniques to produce refine model parameters. The experiments are conducted on datasets of large vocabulary isolated Punjabi lexicons. The simulation result shows the performance improvement using MFCC and DE + HMM technique when compared with RASTA-PLP, PLP using hybrid HMM classifiers.

• V. Bhardwaj, V. Kadyan, A. Singh, & R. Sachdeva, “An experimental framework of speaker independent speech recognition system for Kashmiri language (K-ASR) system using Sphinx.” in International Journal of Emerging Trends in Science and Technology, vol. 4, issue 07, 2017.

  Abstract: Speech to text conversion in various languages have been performed so far but no process has defined for the Kashmiri language. There has been no research done on Kashmiri speech recognition. So in this work, we describe the development as well as implementation of first CMU Sphinx-3 based speech recognizer for the Kashmiri language. Recognition of the words have been done by using hidden markov models (HMMs). Dictionary consists of 100 words, representing Kashmiri digits from one (akh) to hundred (hat). Here, we developed a speaker independent, Kashmiri - Automatic Speech Recognition (KASR) system. The System is trained and tested for 1200 words spoken by 12 male and female speakers. Maximum Accuracy of 78.33% was achieved by the K-ASR system.

• V. Kadyan, A. Singh, and P. Wadhwa (2017) Hindi Dialect (Bangro) Spoken Language Recognition (HD-SLR) System Using Sphinx3. In: Singh R., Choudhury S. (eds) Proceeding of International Conference on Intelligent Communication, Control and Devices. Advances in Intelligent Systems and Computing, vol 479. Springer, Singapore.

  Abstract: A Hindi dialect (Bangro) Spoken Language Recognition (HD-SLR) System is designed to recognize language from a given spoken utterance. Paper focuses on the influence of Hindi dialects, i.e., Haryanvi spoken by males and females of different age groups ranging from 18 to 40 years. The system is trained and tested with the help of Sphinx3 toolkit on Linux platform. Also, it has been tried with semicontinuous speech corpus in clean environment of around 5 h that includes 1000 distinct Hindi dialect words spoken in different parts of Haryana. The dialectal information of the input speech signals is extracted with the help of MFCC technique and the same system is then tested on the basis of utterance level. The Speaker Independent Semicontinuous (SISC) word recognition system has an average of 75–85 % accuracy rate by native and nonnative speakers of Hindi dialect.

• K. Goyal, V. Kadyan and A. Singh “A Survey of Tonal Aspects of Different Languages”, in National Symposium on Computing, Analytics and Networks, NCAN 2017, Chitkara University, Himachal Pradesh, 15 April 2017.

  Abstract: Natural language and human–machine interaction is a very much traversed as well as challenging research domain. However, the main objective is of getting the system that can communicate in well-organized manner with the human, regardless of operational environment. In this paper a systematic survey on Automatic Speech Recognition (ASR) for tonal languages spoken around the globe is carried out. The tonal languages of Asian, Indo-European and African continents are reviewed but the tonal languages of American and Austral-Asian are not reviewed. The most important part of this paper is to present the work done in the previous years on the ASR of Asian continent tonal languages like Chinese, Thai, Vietnamese, Mandarin, Mizo, Bodo and Indo-European continent tonal languages like Punjabi, Lithuanian, Swedish, Croatian and African continent tonal languages like Yoruba and Hausa. Finally, the synthesis analysis is explored based on the findings. Many issues and challenges related with tonal languages are discussed. It is observed that the lot of work have been done for the Asian continent tonal languages i.e. Chinese, Thai, Vietnamese, Mandarin but little work been reported for the Mizo, Bodo, Indo-European tonal languages like Punjabi, Latvian, Lithuanian as well for the African continental tonal languages i.e. Hausa and Yourba.

• Virender Kadyan, Ashish Chopra, “Implementation and Performance analysis of PSTTD system” by Lambert Publication, Germany. (ISBN: 978-3-659-93987-7).

  Abstract: In modern speech recognition systems, there are a set of Feature Extraction Techniques (FET) like Mel-frequency cepstral coefficients (MFCC) or perceptual linear prediction coefficients (PLP) are mainly used. As compared to the conventional FET like LPCC etc, these approaches are provide a better speech signal that contains the relevant information of the speech signal uttered by the speaker during training and testing of the Speech To Text Detection System (STTDS) for different Indian languages. In this dissertation, variation in the parameters values of FET’s like MFCC, PLP are varied at the front end along with dynamic HMM topology at the back end and then the speech signals produce by these techniques are analyzed using HTK toolkit. The cornerstone of all the current state-of-the-art STTDS is the use of HMM acoustic models. In our work the effectiveness of proposed FET(MFCC, PLP features) are tested and the comparison is done among the FET like MFCC and PLP acoustic features to extract the relevant information about what is being spoken from the audio signal and experimental results are computed with varying HMM topology at the back end.

Year 2016

• A. Kaur, A. Singh and V. Kadyan, “Correlative consideration concerning feature extraction techniques for Speech Recognition- a Review”, in (IEEE) ICCPCT at Noorul Islam Centre for Higher Education, Kumaracoil, 18th-19th March 2016.

  Abstract: This paper frames correlation on three feature extraction techniques in ASR system. As compared to primarily used technique called MFCC (Mel Frequency Cepstral Coefficients), PNCC (Power Normalized Cepstral Coefficients) obtains impressive advancement in noisy speech recognition due of its inhibition in high frequency spectrum for human voice. The techniques differ in the way as MFCC uses traditional log nonlinearity and PNCC processing substitute the usage of power-law nonlinearity. Experimental results relay on the fact that PNCC processing provides substantial improvements in recognition accuracy compared to MFCC as well as PLP (Perceptual Linear Prediction) processing for speech recognition in the existence of various types of additive noise and reverberant environments with marginally greater computational cost and the with the usage of clean speech, it does not lowers the decoding accuracy.

• A. Chopra, S. Sharma and V. Kadyan, “Need of Green computing to improve environmental condition in current era”, in (IEEE) ICEEOT at DMI College of Engineering Chennai, 3rd-5th March 2016.

  Abstract: Green computing refers to the process of improving the efficiency of computing devices and reducing its negative impact on mankind and environment. Over the years the idea of green computing has attracted the world due to its environment benefits. At present green computing is under the consideration of businesses organizations and IT industries to improve environmental conditions for the better living of human being. It is an effective approach to protect our environment from the harmful effects of toxic material used during the manufacturing of computing devices. This paper is an attempt to discuss the need of green computing and the steps required to be taken to improve the environmental condition in current era.

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Patents

BALLISTIC PROTECTION DEVICE

• Inventors:Puneet Bawa, Harmanpreet Singh, Pranav Garg, Virender Kadyan
  Patent File Number - 202011054101
  Patent File Date -12-12-2020
  Patent Publication-Date - none
  Abstract: The present disclosure pertains to a ballistic protection device including a sheet, one or more windows configured with the sheet at a first pre-determined position, where the one or more windows facilitate viewing an entity, a linkage assembly coupled between the one or more windows, where the linkage assembly facilitate holding at least one weapon, and where the at least one weapon enables shooting the entity. The linkage assembly includes a rotating base to facilitate rotation of the at least one weapon from a first pre-determined angle to a second pre-determined angle, one or more fasteners configured with the rotating base, where the one or more fasteners enable supporting the at least one weapon on the rotating base ,and where the linkage assembly facilitate mobility of the at least one weapon during targeting and shooting the entity.

SCREWDRIVER WITH MULTIPLE BIT ASSEMBLIES

• Inventors:Puneet Bawa, Pranav Garg, Virender Kadyan, Pranav Kumar
  Patent File Number -202011052427
  Patent File Date -02-12-2020
  Patent Publication Date - none
  Abstract: A multi-bit screwdriver is disclosed. The screwdriver includes an elongate body having a first end, a second end, and a lateral surface between the first end and the second end to form an interior cavity. The screwdriver also includes a plurality of screwdriver bit assemblies disposed on the interior cavity of elongate body. Each of the plurality of screwdriver bit assemblies has a screwdriver bit on one side and an interlocking portion on another side to allow another screwdriver bit assembly of the plurality of screwdriver bit assemblies to interlock with the corresponding screwdriver bit along the lateral surface.

HAND-OPERATED MASSAGER WITH FLUID APPLICATOR

• Inventors: Taniya, Virender Kadyan, Pranav Garg
  Patent File Number - 202011045912
  Patent File Date - 21/10/2020
  Abstract: The present disclosure relates a massaging device, and more particularly to a massager with massaging points that enables the user to massage any part of the body and the massager dispenses fluid to add on the massaging effect

Device For Currency Identification And Notification Using Braille Cells

• Inventors: Puneet Bawa, Virender Kadyan, Pranav Garg
  Patent File Number - 202011039541
  Patent File Date - 16/09/2020
  Patent File Date - none
  Abstract: The present disclosure pertains to a device for currency identification and notification using Braille cells. The device can be configured in the form of a watch having a strap to facilitate tying and untying of the device. The device can operate in three modes -- currency identification mode, time notification mode, and refreshing mode. When the device operates in the currency identification mode, the image acquisition unit can capture images of the currencies, and the captured images can further be processed at the control unit to identify the currencies, and then the Braille cells can be moved in one or more directions to form a pattern corresponding to the identified currencies, where people can touch the pattern and identify the currencies. The device also includes a timing unit that facilitates in notifying time in a similar manner.

Portable Ventilated Universal Laptop Stand(Design Patent)

• Inventors:Puneet Bawa,Pranav Garg,Virender Kadyan,Pranav Kumar
  Patent File Number -332371-001
  Patent File Date -26/08/2020
  Patent File Date - none
  

Height Adjustable Folding Arm Rest Table With Slidable Holders(Design Patent)

• Inventors: Puneet Bawa,Pranav Garg,Virender Kadyan,Pranav Kumar
  Patent File Number - 332372-001
  Patent File Date - 26/08/2020
  Publication Date - none
  

A Marking Device

• Inventors: Puneet Bawa, Virender Kadyan, Sachin Ahuja, Pranav Garg
  Patent File Number - 202011020278
  Patent File Date - 14/05/2020
  Publication Date - none
  Abstract: The present disclosure pertains to a marking device for E presentations. The device includes a set of input units configured to detect one or more operations associated with a user, and correspondingly generate a first set of signals. A control unit operatively coupled with the set of input units, and configured to extract a second set of signals from the first set of signals, where the second set of signals pertain to selection of one or more modes. A set of output units operatively coupled with the control unit, where at least one output unit from the set of output units is configured to operate in at least one mode among the selected one or more modes based on the extracted second set of signals. The device includes at least one input unit which is detachable. The device is portable and multifunctional.

Protective Case

• Inventors: Pranav Garg, Pranav Kumar, Puneet Bawa, Virender Kadyan
  Patent File Number - 202011016321
  Patent File Date - 15/04/2020
  Publication Date - none
  Abstract: The present disclosure describes a protective case for electronic devices such as cell phones. The cover is associated with an air bag along with other mechanical channels or pipes for retaining and supplying gas like carbon dioxide. The case includes the first set of sensors and the second set of sensors with a processing unit which collectively helps in detecting the damage or risk associated with the cell phone. The case protects the device from any internal or external ruining caused during falling or any exposure to harsh elements in a similar situation.

Solar Cooking Tawa

• Inventors: Virender Kadyan, Pranav, Pranav Garg, Lovnish Garg
  Patent File Number - 201911053531
  Patent File Date - 23/12/2019
  Publication Date - none
  Abstract: According to an embodiment, the present disclosure provides an air purifier device. The air purifier device can include a housing comprising an inlet to enable drawing ambient air inside the housing; an inlet pipe configured with the inlet at its one end, wherein a heating element is configured at inner periphery of the inlet pipe to enable heating of the drawn air. An enclosed chamber disposed of inside the housing, and coupled to the other end of the inlet pipe to settle the drawn air to facilitate removing unwanted particles from the settled air thereby cleaning the settled air. An outlet pipe configured with the enclosed chamber at its one end, and configured with an outlet of the housing at its other end to discharge the filtered air through the outlet of the housing.

Apparatus For Spreading An Agricultural Material

• Inventors: Virender Kadyan, Deepika Koundal
  Patent File Number - 201911050411
  Patent File Date - 6/12/2019
  Publication Date - none
  Abstract: According to an embodiment, the present disclosure provides an apparatus for spreading an agricultural material. The apparatus for spreading an agricultural material can include a support structure, a housing having a storage space to store the material, the housing can include an inlet opening to receive the material, and an outlet opening for outflow of the material from the housing, the housing fitted on the support structure such that a gap is created between the support structure and an outlet opening of the housing to allow outflow of the material, a slider plate slidably configured with the outlet opening of the housing. A rotor fitted on the support structure, wherein the rotor is configured such that a rotary part of the rotor is located in the gap for spreading the material coming out from the outlet opening through the gap.

Smart Gas Stove With Control System And Method For Controlling Gas Flow

• Inventors: Virender Kadyan, Puneet Bawa, Santosh Kumar Verma
  Patent File Number - 201911032260
  Patent File Date - 08/08/2019
  Publication Date - none
  Abstract: The present disclosure relates to a gas appliance, and more specifically, to a smart gas stove with control system and method for controlling gas flow and disconnecting the burner automatically in case of liquid spillage and gas leakage.The smart gas stove includes at least one tray which positioned under one or more burners of the smart gas stove. The tray includes one or more valves associated with each of one or more burners, at least one gas leakage detector and a microcontroller. The microcontroller operatively coupled with the one or more valves and the gas leakage detector. The gas leakage detector detects gas leakage in a proximity area of the burner selected from the one or more burners and triggers the microcontroller to control and restrict a gas flow to the burner.

Wireless Charging Device

• Inventors: Virender Kadyan, Pranav Garg, Pranav Kumar, Jashanpreet Kaur
  Patent File Number - 201911048935
  Patent File Date - 28/11/2019
  Publication Date - none
  Abstract: According to an embodiment, the present disclosure provides a wireless charging device. A wireless charging device comprises a primary coil and a secondary coil, a generator operatively coupled with the primary coil and the secondary coil, the generator comprises a stator, an armature, and a shaft, wherein the shaft is configured with the armature; a first rotary disc fitted with the shaft, wherein a plurality of first magnets are disposed at an outer periphery on the first rotary disc; plurality of second magnets are disposed on a second rotary disc at predefined position, wherein the second rotary disc is oriented perpendicular to the first rotary disc such that the plurality of second magnets repels the plurality of first magnets to enable rotatory movement of the first rotary disc, wherein rotation of the second disc provides rotatory movement of the first disc, and wherein rotation of the shaft enables spinning of armature produces electromagnetic induction inside the stator to generate electric charge; wherein the generator transmits electric charge to the primary coil such that the primary coil produces magnetic flux enables the secondary coil to generate electric flux for wireless charging.

System And Method For Cleaning A Board

• Inventors: Virender Kadyan, Rishabh Sharma, Girish Kumar, Santosh Kumar Verma
  Patent File Number - 201911039604
  Patent File Date - 30/09/2019
  Publication Date - none
  Abstract: The present disclosure provides a system and method for cleaning a board. The system includes: a sliding assembly coupled to the board, and having sliding member and cleaning unit coupled to sliding member; an input unit having imaging device configured to receive information associated with the board and generate first set of images associated with the information; and a control unit configured to clean, by using the cleaning unit, the board by activating the sliding assembly; detect, upon generation of the first of images, one or more objects in at least one of the first set of images; generate, by the control unit, metadata associated with at least one of the detected objects to extract a query image from the first set of images based on the metadata; and clean, by using the cleaning unit, based on extraction of the query image, the board.

A Portable Braille Device

• Inventors: Virender Kadyan, Amitoj Singh, Vaibhav
  Patent File Number - 201911015148
  Patent File Date - 15/04/2019
  Publication Date - none
  Abstract: The present disclosure provides a portable braille device, the device includes: a housing; an input unit configured to receive one or more data files, said one or more data files pertaining to one or more characters of a language; a control unit operatively coupled with the input unit, the control unit configured to convert the one or more data files to a corresponding one or more braille files, said one or more braille files pertaining to a corresponding one or more characters of a braille format, wherein the conversion of the one or more data files to a corresponding one or more braille files is based on a stored dataset; and a braille screen having plurality of tactile pixels, the braille screen operatively coupled with the control unit, wherein one or more tactile pixels of the plurality of tactile pixels are engaged to display said one or more braille files.

An Apparatus For Dispensing Plant Nutrient

• Inventors: Virender Kadyan, Deepika Koundal, Jagpreet Sidhu, Amandeep Singh Oberoi
  Patent File Number - 201711034792
  Patent File Date - 29/09/2017
  Publication Date - none
  

Clip Type Laptop Stand (Design Patent)

• Inventors: Jagpreet Sandhu, Amandeep Singh Oberoi, Virender kadyan, Rajinder Sandhu
  Patent File Number - 296000
  Patent File Date - 21/07/2017
  Design Accepted and Published, Journal No is 30/2019 and Journal Date is 26/07/2019
  

Clap Type Laptop Stand (Design Patent)

• Inventors: Jagpreet Sandhu, Amandeep Singh Oberoi, Virender kadyan, Rajinder Sandhu
  Patent File Number - 295998
  Patent File Date - 21/07/2017
  Design Accepted and Published, Journal No is 32/2019 and Journal Date is 09/08/2019
  

A Load Lifting Apparatus

• Inventors: Deepanshu Bhardwaj, Virender Kadyan, Simranpreet Singh Thukral, Atimuqt Dogra
  Patent File Number - 201711045103
  Patent File Date - 15/12/2017
  Publication Date - none
  Abstract: The present disclosure provides a load lifting apparatus. The disclosed apparatus can comprise: a gripper for holding an object to be lifted; a set of sensors coupled with the gripper to sense weight of the object; a control unit operatively coupled with the set of sensors, the control unit is adapted to compare the sensed weight of the object with a predefined weight, wherein based on the comparison if the sensed weight of the object is less than or equal to the pre-defined weight, the control unit generates a first signal, a rotary device operatively coupled with said control unit, said rotary device gets actuated based on said generated first signal, wherein actuation of the rotary device enables movement of said gripper between a first position and a second position to facilitate lifting of the object between the first position and the second position.

Paperless Erasable Magnetic Braille Slate

• Inventors: Amitoj Singh, Virender Kadyan, Vinay Kukreja, Amandeep Singh Oberoi
  Patent File Number - 201611033447
  Patent File Date - 30/09/2016
  Publication Date - none
  Abstract: Disclosed invention consists of a frame with individual blocks of 6 dots arranged in 3 rows and 2 columns, magnetic stylus, Electromagnetic slider of same polarity as of magnetic balls. slider fixed in slider slot at the base of the slate, silicon rubber, top plate with electromagnetic holes carrying opposite charge on the braille slate and arranged in columns and rows , array of extendable plunger , multiple magnetic balls arranged in holes, stylus with magnetic End , gripper and pressure sensing based 5TPI (Five Teeth per Inch) mechanism fitted between the silicon rubber and lower edge of the magnetic braille slate. The electromagnetic slider changes the polarity of magnetic field at the base of the slate so that all the magnetic balls fall down simultaneously in order to provide a clean and erased look to slate for reuse.

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Achievements

Winner of ‘Most International Project’ in University Of Nottingham, China at Global Ingenuity’18 Finals
Dr. Virender Kadyan Wins 1st Prize and is Invited to United Nations Headquarters
Winner at ACM India Chapter Technology Solutions Contest 2019
'Winner' at the Novate+ Himachal Pradesh winning grant of ₹2,50,00
Winner of Punjab Innovation Summit 2019
Speech Lab members presented BrilTab Edukit-1 and Child-Ensign project at UN House, Delhi on 7 Sept 2019
Winner of HACKTIET’19, A 24-Hour Hackathon Organised By DSC, Thapar And GirlScript, Patiala
Winner of Chitkara Master Code Chef - Season 3 (Code Hackathon)
Winners Of UN Influx-Global Hackathon 2017

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